this post was submitted on 11 Oct 2024
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Fuck AI

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As of last week, OpenAI is now worth $157 billion - yet below the hood is a far darker story. In this episode, Ed Zitron explains the cold, hard truth - that OpenAI is a terrible business that burns billions of dollars, and its failure to scale its cloud business tells a dark tale about the wider generative AI industry.

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[–] [email protected] 9 points 3 weeks ago (2 children)

One of the points I find concerningis that businesses built on the current price point for the different models are going to get wiped out when they have to raise prices to keep the lights on.

[–] [email protected] 12 points 3 weeks ago (1 children)

none of them can say they haven't been warned. It's common knowledge that they're haemhorraging money, it's only a matter of time before the investors start wanting some sort of return

[–] FlyingSquid 3 points 3 weeks ago

I just want to know what's going to happen to all the data centers being built to handle all of this needless LLM shit that almost no one wants.

[–] [email protected] 3 points 3 weeks ago (1 children)

"Play stupid games, win stupid prizes" seems to apply here.

[–] [email protected] 1 points 3 weeks ago (1 children)

I think smaller businesses and the true believers are victims of OpenAI and its ilk, and don't necessarily deserve the fallout.

[–] [email protected] 1 points 3 weeks ago

Smaller businesses are the ones who should be watching with a very jaundiced eye that being foisted on them by huge businesses. The huge businesses, you see, are there basically to screw them over and take their stuff.

Smaller businesses should be focused on sustainable income and growth, not the latest in wild tech claims. If they're the latter? They're the lame gazelle in the herd being hunted by lions.

[–] [email protected] 7 points 3 weeks ago* (last edited 3 weeks ago)

Current neural networks do really fancy statistics. To make the model better, you need to make the statistics more precise. Leading to marginal improvements of accuracy requiring exponentially growing marginal amounts of training data. This leads to exponentially decaying marginal utility coupled with exponentially growing marginal expense. Which quickly becomes unsustainable. Edit: On the plus side, this likely means you won't have to give up much utility when the market adjusts.